@inproceedings{a0409015a8a44ec5b46ff9eaed229d40,
title = "A Synthetic Prediction Market for Estimating Confidence in Published Work",
abstract = "Explainably estimating confidence in published scholarly work offers opportunity for faster and more robust scientific progress. We develop a synthetic prediction market to assess the credibility of published claims in the social and behavioral sciences literature. We demonstrate our system and detail our findings using a collection of known replication projects. We suggest that this work lays the foundation for a research agenda that creatively uses AI for peer review.",
author = "Sarah Rajtmajer and Christopher Griffin and Jian Wu and Robert Fraleigh and Laxmaan Balaji and Anna Squicciarini and Anthony Kwasnica and David Pennock and Michael McLaughlin and Timothy Fritton and Nishanth Nakshatri and Arjun Menon and Modukuri, \{Sai Ajay\} and Rajal Nivargi and Xin Wei and \{Lee Giles\}, C.",
note = "Publisher Copyright: Copyright {\textcopyright} 2022, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.; 36th AAAI Conference on Artificial Intelligence, AAAI 2022 ; Conference date: 22-02-2022 Through 01-03-2022",
year = "2022",
month = jun,
day = "30",
language = "English (US)",
series = "Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022",
publisher = "Association for the Advancement of Artificial Intelligence",
pages = "13218--13220",
booktitle = "IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations",
}